A complete understanding of the function of RNA molecules requires a knowledge of the higher order structures (2D and 3D) as well as the characteristics of their primary sequence. RNA structure is important for many functions, including regulation of transcription and translation, catalysis, and transport of proteins across membranes. The understanding of these functions are important for basic biology as well as for bioassays and the development of drugs that can intervene in cases where pathological functionality of these molecules occurs. This may include viruses such as HIV or expression pathways in malignant cells.[unreadable] [unreadable] [unreadable] [unreadable] We have developed and continue to improve upon an RNA folding algorithm (MPGAfold) that uses concepts from genetic algorithms. The algorithm was originally developed on a massively parallel SIMD (16,384 processors) MasPar and currently runs on parallel MIMD supercomputers. MPGAfold can run on a single processor of an SGI OCTANE, a 64 processor SGI ORIGIN 3800 as well as a 512 processor CRAY T3E. A more recent version has been optimized and adapted to run on LINUX clusters, using MPI, such as a 256 processor SGI ALTIX with its high speed interconnect or on less expensive parallel PC-based architectures. The algorithm scales extremely well and is capable of running with hundreds of thousands of population elements on hundreds of physical processors, giving significant structural results when analyzed in the context of population variation. We are able to predict RNA pseudoknots and explore folding pathways that contain multiple functional conformations. In addition, the algorithm contains other features such as a Boltzmann relaxation technique, a choice of different energy rules, the ability to simulate sequential folding as well as sequential processing, forced/suggested and inhibited embedding of helical stems and the visualization of folding dynamics in real time. A new Java-based visualizer for depicting population evolution has also been developed which when coupled with the MPI version of MPGAfold makes the system more user friendly and portable. [unreadable] [unreadable] [unreadable] [unreadable] STRUCTURELAB, the heterogeneous bioinformatical RNA analysis workbench, which permits the use of a broad array of approaches for RNA structure analysis, has been continually enhanced. For example, it can generate refined 3D atomic coordinates of RNA structures along with the visualization of these structures. It also contains a novel interactive visualization methodology, STEM TRACE. This methodology enables the comparison and analysis of multiple sequence RNA folds from a phylogenetic point of view, thus allowing improvement of predicted structural results across a family of sequences. In addition, it permits the visualization of folding pathways when used in conjunction with the genetic algorithm (see above). It is also possible to produce motif patterns so that families of RNA sequences can be explored for common structural elements. In general, STRUCTURELAB and other new tools we have developed, contain several features which when used together, act as set of data mining tools to aid in the discovery of patterns in databases of RNA secondary structures including RNA folding pathways. These systems have been adapted to other environments inside and outside our laboratory and NIH and are available upon request.[unreadable] [unreadable] [unreadable] [unreadable] This system has been employed in studying RNA folding pathways and their functional intermediates as exemplified by the PSTV viroids and the hok/sok plasmid, both of which enter into intermediate states that are important for their life cycle. More recently the folding pathway of the HIV dimerization region has been studied in detail as well as the hepatitis delta virus, interlukin-2, rotavirus and the turnip crinkle virus. We also studied the genetic mechanisms of the viral cardiovirulence phenotype of the coxsackie B viruses which includes mechanisms for transcription attenuation.